Non-communicable diseases (NCDs) are a significant threat to population health. In Saudi Arabia, the burden of NCDs is higher than in developed countries. One of the primary goals for the Saudi Vision 2030 is to increase life expectancy from 74 to 80 by the year 2030. In order to increase life expectancy, much investment is needed to reduce significant threats to mortality such as NCDs. The increasing availability of digital data from different sources opens a new frontier for healthcare research. This study assesses the distribution and the frequency of major NCDs and their risk factors to understand their burden on population health, such as; diabetes, hypertension, and asthma and some of their risk factors, and more importantly this study includes a validation analysis looking at a different sampling approach. Data were collected by an online survey through Absher platform over a period of 11 months. To create a representative survey sample, we constructed sample weights using the Saudi population's regions, gender, nationality, and age group distributions. Weights were used to sample from the survey data randomly. Next, a stratified systematic random sampling was applied with probability proportional to size. Two strata were created, one for males and the other for females. This approach resulted in a random subsample that match the Saudi population. The prevalence of diabetes, hypertension, high cholesterol and asthma was found to be 14.40%, 15.65%, 16.25% & 6.29% respectively. The results suggest that NCDs remain a high burden of population health in Saudi Arabia. As the Kingdom move further to achieve Vision 2030, continuous monitoring of disease prevalence is warranted.

CHRS0762022

https://doi.org/10.60840/nhrsp-a355

Data were collected by an online survey through Absher platform over a period of 11 months, from April 2019 to February 2020. All users (7 million) of the government's e-service portal (ABSHER) received the survey notification once they logged into the website and were invited to participate. A self-administered questionnaire was offered in both Arabic & English through Absher platform to collect the data on a range of demographic variables, chronic diseases, and risk factors associated with these diseases. The survey data were analyzed to explore the main distribution of the participant characteristics, including regions, gender, nationality, and age group distributions. A comparison of participants' characteristics to the population of Saudi Arabia was applied. The Saudi population data were obtained from the 2018 Statistical Yearbook published by Saudi General Authority for Statistics (GASTAT). To create a representative survey sample, we constructed sample weights using the Saudi population's regional, gender, nationality, and age group distributions. Weights were used to sample from the survey data randomly. Next, a stratified systematic random sampling was applied with probability proportional to size. Two strata were created, one for males and the other for females. This approach resulted in a random subsample that match the Saudi population.